1. Field of the Invention
Embodiments of the invention are in the field of robotics. More particularly, embodiments of the invention pertain to a dexterous robotic apparatus, associated methods, and applications thereof and, most particularly, to a two-finger, dexterous robotic hand, associated methods, and applications thereof.
2. Related Art
Grasping and dexterous manipulation rank among the principal grand challenges in robotics. Proposed solutions typically involve complex robot hands that take inspiration from the human hand, often with nine or more independent degrees of freedom.
Engineers have endeavored to replicate the human hand since at least 202 BC, at first only aesthetically, and later with increasing functionality. For a good part of this time, efforts were focused only on prosthetic devices, but starting in the late 1960's concurrent advancements in electronics, computers, and robotics opened the door for research into dexterous hands for robots as well. The competence of the human hand is one of the central evolutionary advantages that humans possess, thus restoring this functionality for amputees and furthering these capabilities in robots are important goals.
One of the central challenges for both prosthetic and robot hands is to achieve dexterous manipulation; i.e., the movement of a grasped object within the workspace of the hand. Since robot hands are not subject to the many design constraints of prosthetics (weight, size, power, controllable degrees of freedom) they have served as the primary platform for grasping and dexterous manipulation research. Greater than one hundred different robot hand designs have been proposed by researchers in the last forty years. While great strides have been made in grasping, the achievement of human-level manipulation by robots has remained elusive.
Dexterous manipulation is a task-centric concept, meaning that a hand can be classified as dexterous through the demonstration of certain in-hand manipulations of an object. Enumerating these requisite manipulation tasks is, however, a topic of some uncertainty. The two prevailing metrics for evaluating robotic dexterous manipulation are:                1. Demonstrations from among several basic classes of in-hand movements, most recently separated into six specific classes for robots: regrasping, in-grasp manipulation, finger gaiting, finger pivoting/tracking, rolling, and sliding.        2. Demonstration of a sufficiently broad set of real world manipulation tasks that are typically some combination of those proposed in the Activities of Daily Living (M. P. Lawton, E. M. Brody, Assessment of older people: self-maintaining and instrumental activities of daily living, The Gerontologist 9, 179-186, 1969), Cutkosky's taxonomy of manufacturing grasps (M. R. Cutkosky, On grasp choice, grasp models, and the design of hands for manufacturing tasks, IEEE Transactions on Robotics and Automation 5, 269-279, 1989), the DARPA ARM-H project announcement challenge tasks (DARPA-BAA-10-29, Autonomous Robotic Manipulation Hardware Track (ARM-H), 2010), or other examples contrived to illustrate the capabilities of a particular hand.        
In 1984, while describing the famous Utah/MIT dexterous robot hand, Jacobsen et al. (S. C. Jacobsen, J. E. Wood, D. R. Knutti, K. B. Biggers, The Utah/MIT dexterous hand: work in progress, IJRR 3, 21-50, 1984) articulated the viewpoint which had been, and which has remained, the longstanding sentiment of researchers in the field: “The natural manipulation system found in humans is complex. . . . It should be expected that the construction of an artificial counterpart will also include significant complexity.” The human hand has 22 degrees of freedom (DOF) and as a result many proposed robot hands have been designed with a similar level of complexity. For those robot hands that do not adhere to anthropomorphism so strictly, designs are typically based on the work of Salisbury (M. T. Mason, J. K. Salisbury Jr., Robot Hands and the Mechanics of Manipulation (The MIT Press, Cambridge, 1985), who found that under certain conditions a minimum of three fingers and nine DOF are needed to satisfactorily perform arbitrary manipulations.
Controlling hands with nine or more DOF can be a difficult task, as evidenced by the large body of work that exists in grasp algorithm research. Some recent work has put forth the view that human-level grasping and manipulation can perhaps be achieved with fewer DOF and fewer actuators by taking advantage of synergies between actuators, and underactuation in mechanical design. Several reported underactuated hands have had success grasping a wide variety of objects with four DOF or fewer, but relatively little progress has been made in the area of dexterous manipulation. Table 1 compares the reported performance of some of the most well known robot hands in order to illuminate the state of the art in robotic dexterous manipulation. Table I compares the reported performance of some of the most well known robot hands in the literature in order to illuminate the state of the art in robotic dexterous manipulation. Among the many robot hands that have been proposed in the literature, the focus of their accompanying publications has often been on the design, manufacturing, and control strategies that are implemented in the given prototype. Relatively few papers present quantitative performance data, and often, terms like dexterous manipulation are used liberally or are simply assumed without explicit demonstration. Furthermore, most all of these robot hands are singular prototypes produced for research purposes and cannot be obtained for further testing. Therefore, in Table I, the columns indicating achieved grasps and manipulations were inferred where possible if they could not be found specifically reported.
TABLE 1COMPARISON OF ROBOTIC HANDS.BasicNo. ofNo. DOFNo. ofGraspsmanipulationsHandImageFingersat JointsActuatorsachievedachieved*Real-world dexterous manipulation achievementsJamHand 22 2†precision and1, 2, 3, 4, 5, 6Operating tweezers, depressing apower graspssyringe, writing with a pen, opening a lock with akey, cracking an egg, assembling two LEGOsin-hand, using chopsticksBarrettHand (29) 37 4precision andunreportedsome manipulation capabilitiespower graspsassumed but not specifically shownDEKA Luke Arm 5un-un-precision and2pouring a grasped measuring cup,(42-44)reportedreportedpower graspsoperating finger nail clippers, pluking a grape,pouring water, more capabilities assumedDLR Hit Hand II (45) 51515human-likeunreportedmanipulation capabilitiesgraspingassumed but not specifically shownassumedGifu Hand (46) 51616human-likeunreportedmanipulation capabilities assumed butgraspingnot specifically shownassumedHarada Hand (47) 514 5precision and2operating wire culters, depressing triggerpower graspson a grasped hand drill, more capabilitiesassumedHigh Speed Hand 38 5precision and1, 2, 5knotting a flexible rope, dribbling a ball,(48-54)power graspsspinning a thin rod between fingers,operating tweezers, folding clothKITECH Hand (55) 41616precision and2, 5rolling and reorienting various objectspower graspsMeka H2 Hand (56) 412 5precision andunreportedmanipulation capabilities assumed butpower graspsnot specifically shownRobonaut2 Hand  51218precision andunreportedflipping switches, pressing buttons, rotating(57-59)power graspsknobs, handling cloth, operating an air flow meter,operating a hand held drill, operating a portablex-ray device, more capabilities assumedSARAH (32, 60-61) 310 2precision andnoneno manipulation capabilities demonstrated orpower graspsdemonstratedassumedSchunk SDH (62) 37 7precision andunreportedsome manipulation capabilities assumed butpower graspsnot specifically shownSDM Hand (31, 63-64) 48 1precision andnoneno manipulation capabilities demonstrated orpower graspsdemonstratedassumedShadow Hand  52020 orhuman-likeunreportedmanipulation capabilities assumed but not(65-67) 40‡graspingspecifically shownassumedSRI Hand (30) 413 5§precision and1, 2turning on a flashlight, more capabilitiespower graspsassumedStanford/JPL 3910precision and1, 2, 4, 5pivoting, rolling and reorienting graspedSalisbury Handpower graspsobjects, more capabilities assumed(23, 68)Utah/MIT Dexterous 41632human-likeunreportedmanipulation capabilities assumed butHand (21, 69)graspingnot specifically shownassumed*inferred where possible: 1) regrasping, 2)in-grasp manipulation, 3) finger gaiting, 4) pivoting, 5) rolling, 6) sliding;†plus two 3-position values;‡20 motors or 40 air muscles;§plus separately controlled brakes at each joint
In view of the aforementioned disadvantages, shortcomings, and problems known in the art, the inventors have recognized the benefits and advantages of, as well as the solutions provided by a dexterous robotic hand and associated methods as embodied herein, and dexterous, robotic grasping/gripping/releasing systems incorporating the embodied dexterous robotic hand and associated methods.